Civil Engineering / İnşaat Mühendisliği
Permanent URI for this collectionhttps://hdl.handle.net/11147/13
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Article Citation - WoS: 29Citation - Scopus: 32Plate Loading Tests on Clay With Construction and Demolition Materials(Springer Verlag, 2021) Cabalar, Ali Fırat; Abdulnafaa, Mohammed Dafer; İşbuğa, VolkanThis study presents a series results of plate loading tests on a clay with various construction and demolition (CD) materials conducted in a large-scale model box and a numerical verification on the use of these material mixtures. The tests have been applied to the clay with three different types of CD materials (concrete, asphalt, and brick) prepared in a reinforced concrete circular box with a diameter of 2.0 m and a depth of 1.5 m. The CD materials were added to the clay with a mix ratio of 10% by dry weight and then compacted at optimum water content (w(opt)) and corresponding maximum dry density (gamma(drymax)). The testing results have indicated that the CD materials increased the ultimate bearing capacity of the clay with a range of 50-75%. Furthermore, a remarkable correlation between the results of plate loading tests and numerical simulations made by a commercial finite element software (Plaxis 2D) was observed for all mixtures tested.Article Citation - WoS: 1Citation - Scopus: 1Generalized Regression Neural Network and Empirical Models To Predict the Strength of Gypsum Pastes Containing Fly Ash and Blast Furnace Slag(Springer Verlag, 2020) Erdem, Tahir Kemal; Cengiz, Okan; Tayfur, GökmenGypsum is widely used in constructions owing to its easy application, zero shrinkage, and excellent fire resistance. Several parameters can affect the properties of gypsum pastes. To study the strength of the gypsum pastes experimentally by trying all these parameters is time-consuming and costly. Therefore, artificial intelligence methods can be very useful to predict the paste strength, which, in turn, can reduce the number of trial batches. Based on experimental data, the generalized regression neural network (GRNN) and empirical models were developed to predict strength of gypsum pastes containing fly ash (FA) and blast furnace slag (BFS). Gypsum content, pozzolan content, curing temperature, curing duration, and testing age constituted the input variables of the models while the paste strength was the target output. The trained and tested GRNN model was found to be successful in predicting strength. Sensitivity analysis by the GRNN model revealed that the curing duration and temperature were important sensitive parameters. In addition to the GRNN model, empirical models were proposed for the strength prediction. The same input variables formed the input vectors of the empirical models. The same dataset used for the calibration of the GRNN model was employed to establish the empirical models by employing genetic algorithm (GA) method. The empirical models were successfully validated. The GRNN and GA_based empirical models were also tested against the multi-linear regression (MLR) and multi-nonlinear regression (MNLR) models. The results showed the outperformance of the GRNN and the GA_based empirical models over the others.Article Citation - WoS: 4Citation - Scopus: 5Pre-Identification Data Merging for Multiple Setup Measurements With Roving References(Springer Verlag, 2020) Ceylan, Hasan; Turan, Gürsoy; Hızal, ÇağlayanOne-time operational modal analysis (OMA) of large civil structures requires measurements of the vibrations, which, according to the number of channels to be measured, are generally expensive and arduous to obtain. In this study, identification of modal parameters of civil structures has been investigated by using multiple setups with a roving reference channel. In this manner, a limited amount of equipment becomes sufficient for OMA of structures. The procedure consists of a transformation function between measurement setups, which transforms all measured data to the time frame of a selected reference setup. To illustrate the procedure, an existing 10 story laboratory shear frame model is considered. A numerical and an experimental investigation have been carried out to identify its modal characteristics. The validity of the procedure has been explained in detail by making use of a coherence function in-between the multi-setup measurements. According to the results, OMA by using only a few sensors with the performed procedure can be equivalent to OMA by using a full measurement setup. Against a common believe, the results of this study reveal that synchronization among the setups does not prominently affect the identification results.Article Citation - WoS: 22Citation - Scopus: 27Micromechanical Modeling of Intrinsic and Specimen Size Effects in Microforming(Springer Verlag, 2018) Yalçınkaya, Tuncay; Özdemir, İzzet; Simonovski, IgorSize effect is a crucial phenomenon in the microforming processes of metallic alloys involving only limited amount of grains. At this scale intrinsic size effect arises due to the size of the grains and the specimen/statistical size effect occurs due to the number of grains where the properties of individual grains become decisive on the mechanical behavior of the material. This paper deals with the micromechanical modeling of the size dependent plastic response of polycrystalline metallic materials at micron scale through a strain gradient crystal plasticity framework. The model is implemented into a Finite Element software as a coupled implicit user element subroutine where the plastic slip and displacement fields are taken as global variables. Uniaxial tensile tests are conducted for microstructures having different number of grains with random orientations in plane strain setting. The influence of the grain size and number on both local and macroscopic behavior of the material is investigated. The attention is focussed on the effect of the grain boundary conditions, deformation rate and the grain size on the mechanical behavior of micron sized specimens. The model is intrinsically capable of capturing both experimentally observed phenomena thanks to the incorporated internal length scale and the crystallographic orientation definition of each grain.Article Citation - WoS: 2Citation - Scopus: 4Removal of Metals and Metalloids From Acidic Mining Lake (aml) Using Olive Oil Solid Waste (osw)(Springer Verlag, 2019) İlay, Remzi; Baba, Alper; Kavdır, YaseminThe acidic mining lakes have low pH values and high metal and metalloid concentrations. In this study, the ability of low-cost olive oil solid waste (OSW) to remove Al, As, Cd, Fe, B and Ti ions from aqueous solutions in short term has been evaluated. Adsorption capacities (mg g−1) of OSW (1:5–1:10 w/v) were 764.06–411.75 for Al, 0.26 for As, 0.07–0.14 for Cd, 2181.5–2406.5 for Fe, 23.70–82.50 for B and 0.12–0.0.34 for Ti. OSW addition increased acidic mine water (AMW) pH from 2.41 to 3.2 with 1:5 and from 2.41 to 2.7 to 1:10 mixing ratio, respectively, after 10 min. The best gradual decrease has been observed with different ratio of OSW applications on B and Ti concentrations. OSW adsorbs 32.41% and 62.68% of B at the ratio of 1:5 and 1:10 and 55.29% and 83.04% of Ti at the ratio of 1:5 and 1:10 (OSW:AMW) mixtures, respectively. The results show that OSW has great potential for metal removal from acidic mine water.Article Citation - WoS: 17Citation - Scopus: 21The Use of Neural Networks for the Prediction of Cone Penetration Resistance of Silty Sands(Springer Verlag, 2017) Erzin, Yusuf; Ecemiş, NurhanIn this study, an artificial neural network (ANN) model was developed to predict the cone penetration resistance of silty sands. To achieve this, the data sets reported by Ecemis and Karaman, including the results of three high-quality field tests, namely piezocone penetration test, pore pressure dissipation tests, and direct push permeability tests performed at 20 different locations on the northern coast of the Izmir Gulf in Turkey, have been used in the development of the ANN model. The ANN model consisted of three input parameters (relative density, fines content, and horizontal coefficient of consolidation) and a single output parameter (normalized cone penetration resistance). The results obtained from the ANN model were compared with those obtained from the field tests. It is found that the ANN model is efficient in determining the cone penetration resistance of silty sands and yields cone penetration resistance values that are very close to those obtained from the field tests. Additionally, several performance indices such as the determination coefficient, variance account for, mean absolute error, root mean square error, and scaled percent error were computed to examine the performance of the ANN model developed. The performance level attained in the ANN model shows that the ANN model developed in this study can be employed for predicting cone penetration of silty sands quite efficiently.Article Citation - WoS: 20Citation - Scopus: 22Modeling of Seawater Intrusion in a Coastal Aquifer of Karaburun Peninsula, Western Turkey(Springer Verlag, 2017) Mansour, Ahmed Y. S.; Baba, Alper; Gündüz, Orhan; Şimşek, Celalettin; Elçi, Alper; Murathan, Alim; Sözbilir, HasanSeawater intrusion is a major problem to freshwater resources especially in coastal areas where fresh groundwater is surrounded and could be easily influenced by seawater. This study presents the development of a conceptual and numerical model for the coastal aquifer of Karareis region (Karaburun Peninsula) in the western part of Turkey. The study also presents the interpretation and the analysis of the time series data of groundwater levels recorded by data loggers. The SEAWAT model is used in this study to solve the density-dependent flow field and seawater intrusion in the coastal aquifer that is under excessive pumping particularly during summer months. The model was calibrated using the average values of a 1-year dataset and further verified by the average values of another year. Five potential scenarios were analyzed to understand the effects of pumping and climate change on groundwater levels and the extent of seawater intrusion in the next 10 years. The result of the analysis demonstrated high levels of electrical conductivity and chloride along the coastal part of the study area. As a result of the numerical model, seawater intrusion is simulated to move about 420 m toward the land in the next 10 years under “increased pumping” scenario, while a slight change in water level and TDS concentrations was observed in “climate change” scenario. Results also revealed that a reduction in the pumping rate from Karareis wells will be necessary to protect fresh groundwater from contamination by seawater.Article Citation - WoS: 1Citation - Scopus: 1Resistive Force Theory-Based Analysis of Magnetically Driven Slender Flexible Micro-Swimmers(Springer Verlag, 2017) Özdemir, İzzetResistive force theory is concise and reliable approach to resolve flow-induced viscous forces on submerged bodies at low Reynolds number flows. In this paper, the theory is adapted for very thin shell-type structures, and a solution procedure within a nonlinear finite element framework is presented. Flow velocity proportional drag forces are treated as configuration-dependent external forces and embedded in a commercial finite element solver (ABAQUS) through user element subroutine. Furthermore, incorporation of magnetic forces induced by external fields on magnetic subdomains of such thin-walled structures is addressed using a similar perspective without resolving the magnetic field explicitly. The treatment of viscous drag forces and the magnetic body couples is done within the same user element formalism. The formulation and the implementation are verified and demonstrated by representative examples including the bidirectional swimming of thin strips with magnetic ends.Article Citation - WoS: 4Citation - Scopus: 4A Numerical Solution Framework for Simultaneous Peeling of Thin Elastic Strips From a Rigid Substrate(Springer Verlag, 2017) Özdemir, İzzetSimultaneous peeling of multiple strips is commonly observed particularly at small-scale detachment processes. Although theoretical treatment of this problem is addressed, numerical solution procedures for geometrically arbitrary multiple-peeling problems are still missing. In this paper, a finite element-based numerical solution procedure for 3-D large displacement multiple-peeling problems is presented. Loading/unloading of peeling strips are expressed in the form of optimality conditions, and the current positions of the peeling fronts are determined locally adapting the multiplicative decomposition and the return mapping algorithm of finite strain plasticity theories. Within an incremental-iterative solution framework, peeling fronts and the current position of other nodes are determined in a staggered way instead of using an active set-based solution algorithm. The effectiveness of the approach is demonstrated by a series of example problems including multiple peeling of an assembly of randomly oriented strips.Article Citation - WoS: 14Citation - Scopus: 17Blowout Mechanism of Alasehir (turkey) Geothermal Field and Its Effects on Groundwater Chemistry(Springer Verlag, 2017) Rabet, Rita Sandrina; Şimşek, Celalettin; Baba, Alper; Murathan, AlimAnatolia region is one of the most seismically active regions in the world and has a considerably high level of geothermal energy potential. Some of these geothermal resources have been used for power generation and direct heating. Most of the high enthalpy geothermal systems are located in western part of Turkey. Alasehir is the most important geothermal site in western part of Turkey. Many geothermal wells have been drilled in Alasehir Plain to produce the geothermal fluid from the deep reservoir in the last 10 years. A blowout accident happened during a geothermal well drilling operation in Alasehir Plain, and significant amount of geothermal fluid surfaced out along the fault zone in three locations. When drilling string entered the reservoir rock about 1000 m, blowout occurred. As the well head preventer system was closed because of the blowout, high-pressure fluid surfaced out along the fault zone cutting the Neogene formation. In order to understand the geothermal fluid effects on groundwater chemistry, physical and chemical compositions of local cold groundwater were monitored from May 2012 to September 2014 in the study area. The geothermal fluid was found to be of Na–HCO3 water type, and especially, arsenic and boron concentrations reached levels as high as 3 and 127 mg/L, respectively. The concentrations of arsenic and boron in the geothermal fluid and groundwater exceeded the maximum allowable limits given in the national and international standards for drinking water quality. According to temporally monitored results, geothermal fluid has extremely high mineral content which influenced the quality of groundwater resources of the area where water resource is commonly used for agricultural irrigation.